733851932

Statistical analysis of spatial and spatio-temporal point patterns / Peter J. Diggle

3. ed.

Englisch

Boca Raton [u.a.] : CRC Press, Taylor & Francis, 2014

XXXI, 267 S. : Ill., graph. Darst.

Erscheint auch als: Online-Ausgabe- Statistical analysis of spatial and spatio-temporal point patterns. - Boca Raton : CRC Press, 2014. - 1 Online-Ressource (XXXI, 267 Seiten)

978-1-4665-6023-9

Preliminary testingMethods for sparsely sampled patterns -- Spatial point processes -- Nonparametric methods -- Models -- Model-fitting using summary descriptions -- Model-fitting using likelihood-based methods -- Point process methods in spatial epidemiology -- Spatio-temporal point processes -- Exploratory analysis -- Empirical models and methods -- Mechanistic models and methods.

*Mustererkennung / Räumliche Statistik

*Spatial analysis (Statistics) ; Statistics ; Spatial analysis (Statistics) ; Statistics ; Spatial analysis (Statistics)

Klassifikation der Library of Congress: QA278.2

Dewey Dezimal-Klassifikation: 519.535; ; 519.5; ; 519.53;

Regensburger Verbund-Klassifikation: SK 850: SA-SP Mathematik / SK Monografien / SK 800 Wahrscheinlichkeitstheorie / Angewandte Statistik, Tabellen

Regensburger Verbund-Klassifikation: SK 950: SA-SP Mathematik / SK Monografien / Mathematische Methoden in den Naturwissenschaften

Mathematics Subject Classification: 62-01

Mathematics Subject Classification: 62M30

Mathematics Subject Classification: 62P10

Mathematics Subject Classification: 62P12

Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author's website --

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